Reducing the babel in plant volatile communication: using the forest to see the trees

While plants of a single species emit a diversity of volatile organic compounds (VOCs) to attract or repel interacting organisms, these specific messages may be lost in the midst of the hundreds of VOCs produced by sympatric plants of different species, many of which may have no signal content. Receivers must be able to reduce the babel or noise in these VOCs in order to correctly identify the message. For chemical ecologists faced with vast amounts of data on volatile signatures of plants in different ecological contexts, it is imperative to employ accurate methods of classifying messages, so that suitable bioassays may then be designed to understand message content. We demonstrate the utility of `Random Forests' (RF), a machine-learning algorithm, for the task of classifying volatile signatures and choosing the minimum set of volatiles for accurate discrimination, using datam from sympatric Ficus species as a case study. We demonstrate the advantages of RF over conventional classification methods such as principal component analysis (PCA), as well as data-mining algorithms such as support vector machines (SVM), diagonal linear discriminant analysis (DLDA) and k-nearest neighbour (KNN) analysis. We show why a tree-building method such as RF, which is increasingly being used by the bioinformatics, food technology and medical community, is particularly advantageous for the study of plant communication using volatiles, dealing, as it must, with abundant noise.

Ecology of the swampy relic forests of Kathalekan from central Western Ghats, India

Introduction of agriculture three millennia ago in Peninsular India’s Western Ghats altered substantially ancient tropical forests. Early agricultural communities, nevertheless, strived to attain symbiotic harmony with nature as evident from prevalence of numerous sacred groves, patches of primeval forests sheltering biodiversity and hydrology. Groves enhanced heterogeneity of landscapes involving elements of successional forests and savannas favouring rich wildlife. A 2.25 km2 area of relic forest was studied at Kathalekan in Central Western Ghats. Interspersed with streams studded with Myristica swamps and blended sparingly with shifting cultivation fallows, Kathalekan is a prominent northernmost relic of southern Western Ghat vegetation. Trees like Syzygium travancoricum (Critically Endangered), Myristica magnifica (Endangered) and Gymnacranthera canarica (Vulnerable) and recently reported Semecarpus kathalekanensis, are exclusive to stream/swamp forest (SSF). SSF and non-stream/swamp forest (NSSF) were studied using 18 transects covering 3.6 ha. Dipterocarpaceae, its members seldom transgressing tropical rain forests, dominate SSF (21% of trees) and NSSF (27%). The ancient Myristicaceae ranks high in tree population (19% in SSF and 8% in NSSF). Shannon-Weiner diversity for trees is higher (>3) in six NSSF transects compared to SSF (<3). Higher tree endemism (45%), total endemic tree population (71%) and significantly higher above ground biomass (349 t/ha) cum carbon sequestration potential (131 t/ha) characterizes SSF. Faunal richness is evident from amphibians (35 species - 26 endemics, 11 in IUCN Red List). This study emphasizes the need for bringing to light more of relic forests for their biodiversity, carbon sequestration and hydrology. The lives of marginal farmers and forest tribes can be uplifted through partnership in carbon credits, by involving them in mitigating global climatic change through conservation and restoration of high biomass watershed forests.

Optimal management of conflicting species: Grey seal (Halichoerus grypus) and Atlantic salmon (Salmo salar) in the Baltic Sea

The objective of this thesis is to examine the economic effects in the conflict between grey seal population and the salmon fishery in the Baltic Sea. We will formulate a bioeconomic model which provides new insights on the optimal management of Atlantic salmon with respect to the effects brought about by the grey seal population. As the catch losses caused by seals have an effect on salmon fishery in Baltic, we will study how seal population affects the present value of the salmon fishery. The study considers the Finnish coastal trap net fishery. The bioeconomic model considers a scenario of sole salmon fishery and a scenario of salmon fishery affected by the grey seal population. On the basis of these scenarios, a seal compensation scheme is introduced. We can observe a significant economic seal-induced effect on the salmon fishery. The results suggest that the present seal compensation scheme emploid by the Finnish government is suboptimal. This thesis is part of the TARMO –project, in which the conflict between grey seal population and salmon fishery is studied using the methods of environmental economics.

Forest governance and climate change adaptation : Case studies of four African countries

Africa is threatened by climate change. The adaptive capacity of local communities continues to be weakened by ineffective and inefficient livelihood strategies and inappropriate development interventions. One of the greatest challenges for climate change adaptation in Africa is related to the governance of natural resources used by vulnerable poor groups as assets for adaptation. Practical and good governance activities for adaptation in Africa is urgently and much needed to support adaptation actions, interventions and planning. The adaptation role of forests has not been as prominent in the international discourse and actions as their mitigation role. This study therefore focused on the forest as one of the natural resources used for adaptation. The general objective of this research was to assess the extent to which cases of current forest governance practices in four African countries Burkina Faso, The Democratic Republic of Congo (DRC), Ghana and Sudan are supportive to the adaptation of vulnerable societies and ecosystems to impacts of climate change. Qualitative and quantitative analyses from surveys, expert consultations and group discussions were used in analysing the case studies. The entire research was guided by three conceptual sets of thinking forest governance, climate change vulnerability and ecosystem services. Data for the research were collected from selected ongoing forestry activities and programmes. The study mainly dealt with forest management policies and practices that can improve the adaptation of forest ecosystems (Study I) and the adaptive capacity through the management of forest resources by vulnerable farmers (Studies II, III, IV and V). It was found that adaptation is not part of current forest policies, but, instead, policies contain elements of risk management practices, which are also relevant to the adaptation of forest ecosystems. These practices include, among others, the management of forest fires, forest genetic resources, non-timber resources and silvicultural practices. Better livelihood opportunities emerged as the priority for the farmers. These vulnerable farmers had different forms of forest management. They have a wide range of experience and practical knowledge relevant to ensure and achieve livelihood improvement alongside sustainable management and good governance of natural resources. The contributions of traded non-timber forest products to climate change adaptation appear limited for local communities, based on their distribution among the stakeholders in the market chain. Plantation (agro)forestry, if well implemented and managed by communities, has a high potential in reducing socio-ecological vulnerability by increasing the food production and restocking degraded forest lands. Integration of legal arrangements with continuous monitoring, evaluation and improvement may drive this activity to support short, medium and long term expectations related to adaptation processes. The study concludes that effective forest governance initiatives led by vulnerable poor groups represent one practical way to improve the adaptive capacities of socio-ecological systems against the impacts of climate change in Africa.

How the development of condensation particle counters is reforming our view on atmospheric nucleation

Aerosol particles deteriorate air quality, atmospheric visibility and our health. They affect the Earth s climate by absorbing and scattering sunlight, forming clouds, and also via several feed-back mechanisms. The net effect on the radiative balance is negative, i.e. cooling, which means that particles counteract the effect of greenhouse gases. However, particles are one of the poorly known pieces in the climate puzzle. Some of the airborne particles are natural, some anthropogenic; some enter the atmosphere in particle form, while others form by gas-to-particle conversion. Unless the sources and dynamical processes shaping the particle population are quantified, they cannot be incorporated into climate models. The molecular level understanding of new particle formation is still inadequate, mainly due to the lack of suitable measurement techniques to detect the smallest particles and their precursors. This thesis has contributed to our ability to measure newly formed particles. Three new condensation particle counter applications for measuring the concentration of nano-particles were developed. The suitability of the methods for detecting both charged and electrically neutral particles and molecular clusters as small as 1 nm in diameter was thoroughly tested both in laboratory and field conditions. It was shown that condensation particle counting has reached the size scale of individual molecules, and besides measuring the concentration they can be used for getting size information. In addition to atmospheric research, the particle counters could have various applications in other fields, especially in nanotechnology. Using the new instruments, the first continuous time series of neutral sub-3 nm particle concentrations were measured at two field sites, which represent two different kinds of environments: the boreal forest and the Atlantic coastline, both of which are known to be hot-spots for new particle formation. The contribution of ions to the total concentrations in this size range was estimated, and it could be concluded that the fraction of ions was usually minor, especially in boreal forest conditions. Since the ionization rate is connected to the amount of cosmic rays entering the atmosphere, the relative contribution of neutral to charged nucleation mechanisms extends beyond academic interest, and links the research directly to current climate debate.

Markov random fields and spatial smoothing in improving of forest inventory estimates

Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.

CSR in forest industry – Case study of reporting and implementation of social responsibility in three international companies

Corporate Social Responsibility (CSR) has become increasingly important topic in forest industries, and other global companies, in recent years. Globalisation, faster information delivery and demand for sustainable development have set new challenges for global companies in their business operations. Also the importance of stakeholder relations, and pressure to become more transparent has increased in the forest industries. Three dimensions of corporate responsibility economic, environmental and social, are often included in the concept of CSR. Global companies mostly claim that these dimensions are equally important. This study analyses CSR in forest industry and has focus on reporting and implementation of social responsibility in three international companies. These case-companies are Stora Enso, SCA and Sappi, and they have different geographical base, product portfolios and therefore present interesting differences about forest industry strategy and CSR. Global Reporting Initiative (GRI) has created the most known and used reporting framework in CSR reporting. GRI Guidelines have made CSR reporting a uniform function, which can also be measured between companies and different sectors. GRI Guidelines have also made it possible to record and control CSR data in the companies. In recent years the use of GRI Guidelines has increased substantially. Typically CSR reporting on economic and environmental responsibility have been systematic in the global companies and often driven by legistlation and other regulations. However the social responsibility has been less regulated and more difficult to compare. Therefore it has previously been often less focused in the CSR reporting of the global companies. The implementation and use of GRI Guidelines have also increased dialogue on social responsibility issues and stakeholder management in global companies. This study analyses the use of GRI´s framework in the forest industry companies´ CSR reporting. This is a qualitative study and the disclosure of data is empricially analysed using content analysis. Content analysis has been selected as a method for this study because it makes it possible to use different sources of information. The data of this study consists of existing academic literature of CSR, sustainability reports of thecase-companies during 2005-2009, and the semi-structured interviews with company representatives. Different sources provide the possibility to look at specific subject from more than one viewpoint. The results of the study show that all case-companies have relatively common themes in their CSR disclosure, and the differences rise mainly from their product-portfolios, and geographic base. Social impacts to local communities, in the CSR of the companies, were mainly dominated by issues concerning creating wealth to the society and impacting communities through creation of work. The comparability of the CSR reporting, and especially social indicators increased significally from 2007 onwards in all case-companies. Even though the companies claim that three dimensions of CSR economic, environmental and social are equally important economic issues and profit improvement still seem to drive most of the operations in the global companies. Many issues that are covered by laws and regulations are still essentially presented as social responsibility in CSR. However often the unwelcome issues in companies like closing operations are covered just briefly, and without adequate explanation. To make social responsibility equally important in the CSR it would demand more emphasis from all the case-companies. A lot of emphasis should be put especially on the detail and extensiveness of the social reponsibility content in the CSR.

Effect of soil preparation of boreal spruce forest on air and soil temperature conditions in forest regeneration areas.

The effect of scarification, ploughing and cross-directional plouhing on temperature conditions in the soil and adjacent air layer have been studied during 11 consecutive growth periods by using an unprepared clear-cut area as a control site. The maximum and minimum temperatures were measured daily in the summer months, and other temperature observations were made at four-hour intervals by means of a Grant measuring instrument. The development of the seedling stand was also followed in order to determine its shading effect on the soil surface. Soil preparation decreased the daily temperature amplitude of the air at the height of 10 cm. The maximum temperatures on sunny days were lower in the tilts of the ploughed and in the humps of the cross-directional ploughed sites compared with the unprepared area. Correspondingly, the night temperatures were higher and so the soil preparation considerably reduced the risk of night frost. In the soil at the depth of 5 cm, soil preparation increased daytime temperatures and reduced night temperatures compared with unprepared area. The maximum increase in monthly mean temperatures was almost 5 °C, and the daily variation in the surface parts of the tilts and humps increased so that excessively high temperatures for the optimal growth of the root system were measured from time to time. The temperature also rose at the depths of 50 and 100 cm. Soil preparation also increased the cumulative temperature sum. The highest sums accumulated during the summer months were recorded at the depth of 5 cm in the humps of cross-directional ploughed area (1127 dd.) and in the tilts of the ploughed area (1106 dd.), while the corresponding figure in the unprepared soil was 718 dd. At the height of 10 cm the highest temperature sum was 1020 dd. in the hump, the corresponding figure in the unprepared area being 925 dd. The incidence of high temperature amplitudes and percentage of high temperatures at the depth of 5 cm decreased most rapidly in the humps of cross-directional ploughed area and in the ploughing tilts towards the end of the measurement period. The decrease was attributed principally to the compressing of tilts, the ground vegetation succession and the growth of seedlings. The mean summer temperature in the unprepared area was lower than in the prepared area and the difference did not diminish during the period studied. The increase in temperature brought about by soil preparation thus lasts at least more than 10 years.

Understorey vegetation as an indicator of forest site potential in Southern Finland.

The relationship between site characteristics and understorey vegetation composition was analysed with quantitative methods, especially from the viewpoint of site quality estimation. Theoretical models were applied to an empirical data set collected from the upland forests of southern Finland comprising 104 sites dominated by Scots pine (Pinus sylvestris L.), and 165 sites dominated by Norway spruce (Picea abies (L.) Karsten). Site index H100 was used as an independent measure of site quality. A new model for the estimation of site quality at sites with a known understorey vegetation composition was introduced. It is based on the application of Bayes' theorem to the density function of site quality within the study area combined with the species-specific presence-absence response curves. The resulting posterior probability density function may be used for calculating an estimate for the site variable. Using this method, a jackknife estimate of site index H100 was calculated separately for pine- and spruce-dominated sites. The results indicated that the cross-validation root mean squared error (RMSEcv) of the estimates improved from 2.98 m down to 2.34 m relative to the "null" model (standard deviation of the sample distribution) in pine-dominated forests. In spruce-dominated forests RMSEcv decreased from 3.94 m down to 3.16 m. In order to assess these results, four other estimation methods based on understorey vegetation composition were applied to the same data set. The results showed that none of the methods was clearly superior to the others. In pine-dominated forests, RMSEcv varied between 2.34 and 2.47 m, and the corresponding range for spruce-dominated forests was from 3.13 to 3.57 m.

Non-industrial private forest landowners’ choices of timber management strategies and potential allowable cut.

In the study, the potential allowable cut in the district of Pohjois-Savo - based on the non-industrial private forest landowners' (NIPF) choices of timber management strategies - was clarified. Alternative timber management strategies were generated, and the choices and factors affecting the choices of timber management strategies by NIPF landowners were studied. The choices of timber management strategies were solved by maximizing the utility functions of the NIPF landowners. The parameters of the utility functions were estimated using the Analytic Hierarchy Process (AHP). The level of the potential allowable cut was compared to the cutting budgets based on the 7th and 8th National Forest Inventories (NFI7 and NFI8), to the combining of private forestry plans, and to the realized drain from non-industrial private forests. The potential allowable cut was calculated using the same MELA system as has been used in the calculation of the national cutting budget. The data consisted of the NIPF holdings (from the TASO planning system) that had been inventoried compartmentwise and had forestry plans made during the years 1984-1992. The NIPF landowners' choices of timber management strategies were clarified by a two-phase mail inquiry. The most preferred strategy obtained was "sustainability" (chosen by 62 % of landowners). The second in order of preference was "finance" (17 %) and the third was "saving" (11 %). "No cuttings", and "maximum cuttings" were the least preferred (9 % and 1 %, resp.). The factors promoting the choices of strategies with intensive cuttings were a) "farmer as forest owner" and "owning fields", b) "increase in the size of the forest holding", c) agriculture and forestry orientation in production, d) "decreasing short term stumpage earning expectations", e) "increasing intensity of future cuttings", and f) "choice of forest taxation system based on site productivity". The potential allowable cut defined in the study was 20 % higher than the average of the realized drain during the years 1988-1993, which in turn, was at the same level as the cutting budget based on the combining of forestry plans in eastern Finland. Respectively, the potential allowable cut defined in the study was 12 % lower than the NFI8-based greatest sustained allowable cut for the 1990s. Using the method presented in this study, timber management strategies can be clarified for non-industrial private forest landowners in different parts of Finland. Based on the choices of timber managemet strategies, regular cutting budgets can be calculated more realistically than before.

Non-industrial private forest landowners’ choices of timber management strategies.

The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.

A participatory approach to tactical forest planning.

The paper examines the needs, premises and criteria for effective public participation in tactical forest planning. A method for participatory forest planning utilizing the techniques of preference analysis, professional expertise and heuristic optimization is introduced. The techniques do not cover the whole process of participatory planning, but are applied as a tool constituting the numerical core for decision support. The complexity of multi-resource management is addressed by hierarchical decision analysis which assesses the public values, preferences and decision criteria toward the planning situation. An optimal management plan is sought using heuristic optimization. The plan can further be improved through mutual negotiations, if necessary. The use of the approach is demonstrated with an illustrative example, it's merits and challenges for participatory forest planning and decision making are discussed and a model for applying it in general forest planning context is depicted. By using the approach, valuable information can be obtained about public preferences and the effects of taking them into consideration on the choice of the combination of standwise treatment proposals for a forest area. Participatory forest planning calculations, carried out by the approach presented in the paper, can be utilized in conflict management and in developing compromises between competing interests.

Factors affecting partitioning of private forest holdings in Finland.

Questions of the small size of non-industrial private forest (NIPF) holdings in Finland are considered and factors affecting their partitioning are analyzed. This work arises out of Finnish forest policy statements in which the small average size of holdings has been seen to have a negative influence on the economics of forestry. A survey of the literature indicates that the size of holdings is an important factor determining the costs of logging and silvicultural operations, while its influence on the timber supply is slight. The empirical data are based on a sample of 314 holdings collected by interviewing forest owners in the years 1980-86. In 1990-91 the same holdings were resurveyed by means of a postal inquiry and partly by interviewing forest owners. The principal objective in compiling the data is to assist in quantifying ownership factors that influence partitioning among different kinds of NIPF holdings. Thus the mechanism of partitioning were described and a maximum likelihood logistic regression model was constructed using seven independent holding and ownership variables. One out of four holdings had undergone partitioning in conjunction with a change in ownership, one fifth among family owned holdings and nearly a half among jointly owned holdings. The results of the logistic regression model indicate, for instance, that the odds on partitioning is about three times greater for jointly owned holdings than for family owned ones. Also, the probabilities of partitioning were estimated and the impact of independent dichotomous variables on the probability of partitioning ranged between 0.02 and 0.10. The low value of the Hosmer-Lemeshow test statistic indicates a good fit of the model and the rate of correct classification was estimated to be 88 per cent with a cutoff point of 0.5. The average size of holdings undergoing ownership changes decreased from 29.9 ha to 28.7 ha over the approximate interval 1983-90. In addition, the transition probability matrix showed that the trends towards smaller size categories mostly involved in the small size categories, less than 20 ha. The results of the study can be used in considering the effects of the small size of holdings for forestry and if the purpose is to influence partitioning through forest or rural policy.